Designing Samples Statistical techniques for producing data open the door to formal statistical inference, which answers specific questions with a known.

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Presentation transcript:

Designing Samples Statistical techniques for producing data open the door to formal statistical inference, which answers specific questions with a known degree of confidence.

Designing Samples Population – the entire group of individuals about which we want information. Sample – the part of the population that we actually examine in order to gather information. Census – enumerates everything in the population. (attempts to contact every individual in the entire population).

Designing Samples Sampling involves studying a part in order to gain information about the whole. Sample design is the method used to choose the sample from the population. Bias is the systematic favoring of one outcome.

Poor design can lead to bias! A voluntary response sample consists of people who choose themselves by responding to a general appeal. A convenience sample chooses the individuals easiest to reach.

Poor design can lead to bias! Undercoverage occurs when some groups in the population are left out of the process of choosing the sample. Nonresponse occurs when an individual chosen for the sample cannot be contacted or refuses to cooperate.

Poor design can lead to bias! Response bias can be caused by the behavior of the respondent or of the interviewer. Wording can also cause bias with confusing or leading questions.